Showing papers on "Solar power published in 2014"

A metal-free organic–inorganic aqueous flow battery

Abstract: Flow batteries, in which the electro-active components are held in fluid form external to the battery itself, are attractive as a potential means for regulating the output of intermittent renewable sources of electricity; an aqueous flow battery based on inexpensive commodity chemicals is now reported that also has the virtue of enabling further improvement of battery performance through organic chemical design. Flow batteries differ from the conventional type in that the electro-active components of flow batteries are held in fluid form external to the battery itself, enabling such systems to store arbitrarily large amounts of energy. Flow batteries are therefore attractive as a potential means for regulating the output of intermittent sources of electricity such as wind or solar power. But an important limitation of most such systems is the abundance and cost of the electro-active materials. To overcome this limitation, Brian Huskinson and colleagues have developed an aqueous flow battery on the basis of inexpensive, non-metallic commodity chemicals, with the added advantage of enabling the tuning of key battery properties through chemical design. As the fraction of electricity generation from intermittent renewable sources—such as solar or wind—grows, the ability to store large amounts of electrical energy is of increasing importance. Solid-electrode batteries maintain discharge at peak power for far too short a time to fully regulate wind or solar power output1,2. In contrast, flow batteries can independently scale the power (electrode area) and energy (arbitrarily large storage volume) components of the system by maintaining all of the electro-active species in fluid form3,4,5. Wide-scale utilization of flow batteries is, however, limited by the abundance and cost of these materials, particularly those using redox-active metals and precious-metal electrocatalysts6,7. Here we describe a class of energy storage materials that exploits the favourable chemical and electrochemical properties of a family of molecules known as quinones. The example we demonstrate is a metal-free flow battery based on the redox chemistry of 9,10-anthraquinone-2,7-disulphonic acid (AQDS). AQDS undergoes extremely rapid and reversible two-electron two-proton reduction on a glassy carbon electrode in sulphuric acid. An aqueous flow battery with inexpensive carbon electrodes, combining the quinone/hydroquinone couple with the Br2/Br− redox couple, yields a peak galvanic power density exceeding 0.6 W cm−2 at 1.3 A cm−2. Cycling of this quinone–bromide flow battery showed >99 per cent storage capacity retention per cycle. The organic anthraquinone species can be synthesized from inexpensive commodity chemicals8. This organic approach permits tuning of important properties such as the reduction potential and solubility by adding functional groups: for example, we demonstrate that the addition of two hydroxy groups to AQDS increases the open circuit potential of the cell by 11% and we describe a pathway for further increases in cell voltage. The use of π-aromatic redox-active organic molecules instead of redox-active metals represents a new and promising direction for realizing massive electrical energy storage at greatly reduced cost.

A nanophotonic solar thermophotovoltaic device

Abstract: The most common approaches to generating power from sunlight are either photovoltaic, in which sunlight directly excites electron-hole pairs in a semiconductor, or solar-thermal, in which sunlight drives a mechanical heat engine. Photovoltaic power generation is intermittent and typically only exploits a portion of the solar spectrum efficiently, whereas the intrinsic irreversibilities of small heat engines make the solar-thermal approach best suited for utility-scale power plants. There is, therefore, an increasing need for hybrid technologies for solar power generation. By converting sunlight into thermal emission tuned to energies directly above the photovoltaic bandgap using a hot absorber-emitter, solar thermophotovoltaics promise to leverage the benefits of both approaches: high efficiency, by harnessing the entire solar spectrum; scalability and compactness, because of their solid-state nature; and dispatchablility, owing to the ability to store energy using thermal or chemical means. However, efficient collection of sunlight in the absorber and spectral control in the emitter are particularly challenging at high operating temperatures. This drawback has limited previous experimental demonstrations of this approach to conversion efficiencies around or below 1% (refs 9, 10, 11). Here, we report on a full solar thermophotovoltaic device, which, thanks to the nanophotonic properties of the absorber-emitter surface, reaches experimental efficiencies of 3.2%. The device integrates a multiwalled carbon nanotube absorber and a one-dimensional Si/SiO2 photonic-crystal emitter on the same substrate, with the absorber-emitter areas optimized to tune the energy balance of the device. Our device is planar and compact and could become a viable option for high-performance solar thermophotovoltaic energy conversion.

Review of High-Temperature Central Receiver Designs for Concentrating Solar Power

Abstract: This paper reviews central receiver designs for concentrating solar power applications with high-temperature power cycles Desired features include low-cost and durable materials that can withstand high concentration ratios (~1000 suns), heat-transfer fluids that can withstand temperatures >650 °C, high solar absorptance, and low radiative and convective heat losses leading to a thermal efficiency >90% Different receiver designs are categorized and evaluated in this paper: (1) gas receivers, (2) liquid receivers, and (3) solid particle receivers For each design, the following information is provided: general principle and review of previous modeling and testing activities, expected outlet temperature and thermal efficiency, benefits, perceived challenges, and research needs Emerging receiver designs that can enable higher thermal-to-electric efficiencies (50% or higher) using advanced power cycles such as supercritical CO 2 closed-loop Brayton cycles include direct heating of CO 2 in tubular receiver designs (external or cavity) that can withstand high internal fluid pressures (~20 MPa) and temperatures (~700 °C) Indirect heating of other fluids and materials that can be stored at high temperatures such as advanced molten salts, liquid metals, or solid particles are also being pursued, but challenges include stability, heat loss, and the need for high-temperature heat exchangers

Sub-150 °C processed meso-superstructured perovskite solar cells with enhanced efficiency

Abstract: The ability to process amorphous or polycrystalline solar cells at low temperature (<150 °C) opens many possibilities for substrate choice and monolithic multijunction solar cell fabrication. Organometal trihalide perovskite solar cells have evolved rapidly over the last two years, and the CH3NH3PbX3 (X = Cl, I or Br) material is processed at low temperature. However the first embodiments of the solar cell were composed of high temperature processed (500 °C) compact and mesoporous layers of TiO2. The sintering of the mesoporous TiO2 has been negated by replacing this with a mesoporous insulating scaffold in the meso-superstructured solar cell (MSSC), yet the high temperature processed compact TiO2 layer still persists in the most efficient devices. Here we have realised a low temperature route for compact TiO2, tailored for perovskite MSSC operation. With our optimized formulation we demonstrate full sun solar power conversion efficiencies of up to 15.9% in an all low temperature processed solar cell.

Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

Abstract: Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Smart home energy management system including renewable energy based on ZigBee and PLC

Abstract: This paper describes smart home energy management system (HEMS) that includes both energy consumption and renewable energy generation. ZigBee is used to measure and transfer the power and energy of home appliances at the outlets and the lights. Power line communication is adopted to monitor solar panels. By considering both energy consumption and generation simultaneously, the proposed HEMS can optimize home energy use and result in energy cost saving.

Triplet–triplet annihilation photon-upconversion: towards solar energy applications

Abstract: Solar power production and solar energy storage are important research areas for development of technologies that can facilitate a transition to a future society independent of fossil fuel based energy sources. Devices for direct conversion of solar photons suffer from poor efficiencies due to spectrum losses, which are caused by energy mismatch between the optical absorption of the devices and the broadband irradiation provided by the sun. In this context, photon-upconversion technologies are becoming increasingly interesting since they might offer an efficient way of converting low energy solar energy photons into higher energy photons, ideal for solar power production and solar energy storage. This perspective discusses recent progress in triplet-triplet annihilation (TTA) photon-upconversion systems and devices for solar energy applications. Furthermore, challenges with evaluation of the efficiency of TTA-photon-upconversion systems are discussed and a general approach for evaluation and comparison of existing systems is suggested.

DC Microgrid for Wind and Solar Power Integration

Abstract: Operational controls are designed to support the integration of wind and solar power within microgrids. An aggregated model of renewable wind and solar power generation forecast is proposed to support the quantification of the operational reserve for day-ahead and real-time scheduling. Then, a droop control for power electronic converters connected to battery storage is developed and tested. Compared with the existing droop controls, it is distinguished in that the droop curves are set as a function of the storage state-of-charge (SOC) and can become asymmetric. The adaptation of the slopes ensures that the power output supports the terminal voltage while at the same keeping the SOC within a target range of desired operational reserve. This is shown to maintain the equilibrium of the microgrid's real-time supply and demand. The controls are implemented for the special case of a dc microgrid that is vertically integrated within a high-rise host building of an urban area. Previously untapped wind and solar power are harvested on the roof and sides of a tower, thereby supporting delivery to electric vehicles on the ground. The microgrid vertically integrates with the host building without creating a large footprint.

The Merit-Order Effect in the Italian Power Market: The Impact of Solar and Wind Generation on National Wholesale Electricity Prices

Abstract: Italy promoted one of the most generous renewable support schemes worldwide which resulted in a high increase of solar power generation. We analyze the Italian day-ahead wholesale electricity market, finding empirical evidence of the merit-order effect. Over the period 2005-2013 an increase of 1 GWh in the hourly average of daily production from solar and wind sources has, on average, reduced wholesale electricity prices by respectively 2.3 €/MWh and 4.2 €/MWh and has amplified their volatility. The impact on prices has decreased over time in correspondence with the increase in solar and wind electricity production. We estimate that, over the period 2009-2013, solar production has generated higher monetary savings than wind production, mainly because the former is more prominent than the latter. However, in the solar case, monetary savings are not sufficient to compensate the cost of the related supporting schemes which are entirely internalized within end-user tariffs, causing a reduction of the consumer surplus, while the opposite occurs in the case of wind.

A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects

Abstract: In the context of the current rapid development of large-scale solar power projects, the accuracy of the modeled radiation datasets regularly used by many different interest groups is of the utmost importance. This process requires careful validation, normally against high-quality measurements. Some guidelines for a successful validation are reviewed here, not just from the standpoint of solar scientists but also of non-experts with limited knowledge of radiometry or solar radiation modeling. Hence, validation results and performance metrics are reported as comprehensively as possible. The relationship between a desirable lower uncertainty in solar radiation data, lower financial risks, and ultimately better bankability of large-scale solar projects is discussed. A description and discussion of the performance indicators that can or should be used in the radiation model validation studies are developed here. Whereas most indicators are summary statistics that attempt to synthesize the overall performance of a model with only one number, the practical interest of more elaborate metrics, particularly those derived from the Kolmogorov–Smirnov test, is discussed. Moreover, the important potential of visual indicators is also demonstrated. An example of application provides a complete performance analysis of the predictions of clear-sky direct normal irradiance obtained with six models of the literature at Tamanrasset, Algeria, where high-turbidity conditions are frequent.

Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States

Abstract: Commonly considered strategies for reducing the environmental impact of light-duty transportation include using alternative fuels and improving vehicle fuel economy. We evaluate the air quality-related human health impacts of 10 such options, including the use of liquid biofuels, diesel, and compressed natural gas (CNG) in internal combustion engines; the use of electricity from a range of conventional and renewable sources to power electric vehicles (EVs); and the use of hybrid EV technology. Our approach combines spatially, temporally, and chemically detailed life cycle emission inventories; comprehensive, fine-scale state-of-the-science chemical transport modeling; and exposure, concentration–response, and economic health impact modeling for ozone (O3) and fine particulate matter (PM2.5). We find that powering vehicles with corn ethanol or with coal-based or “grid average” electricity increases monetized environmental health impacts by 80% or more relative to using conventional gasoline. Conversely, EVs powered by low-emitting electricity from natural gas, wind, water, or solar power reduce environmental health impacts by 50% or more. Consideration of potential climate change impacts alongside the human health outcomes described here further reinforces the environmental preferability of EVs powered by low-emitting electricity relative to gasoline vehicles.

Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models

Abstract: The prediction of solar radiation is important for several applications in renewable energy research. Solar radiation is predicted by a number of solar radiation models both conventional and Artificial Neural Network (ANN) based models. There are a number of meteorological and geographical variables which affect solar radiation prediction, so identification of suitable variables for accurate solar radiation prediction is an important research area. With this main objective, Waikato Environment for Knowledge Analysis (WEKA) software is applied to 26 Indian locations having different climatic conditions to find most influencing input parameters for solar radiation prediction in ANN models. The input parameters identified are latitude, longitude, temperature, maximum temperature, minimum temperature, altitude and sunshine hours for different cities of India. In order to check the prediction accuracy using the identified parameters, three Artificial Neural Network (ANN) models are developed (ANN-1, ANN-2 and ANN-3). The maximum MAPE for ANN-1, ANN-2 and ANN-3 models are found to be 20.12%, 6.89% and 9.04% respectively, showing 13.23% improved prediction accuracy of the ANN-2 model which utilizes temperature, maximum temperature, minimum temperature, height above sea level and sunshine hours as input variables in comparison to the ANN-1 model. The WEKA identifies temperature, maximum temperature, minimum temperature, altitude and sunshine hours as the most relevant input variables and latitude, longitude as the least influencing variables in solar radiation prediction. The methodology is also used to identify the solar energy potential of Western Himalayan state of Himachal Pradesh, India. The results show good solar potential with yearly solar radiation variation as 3.59–5.38 kWh/m2/day for a large number of solar applications including solar power generation in this region.

The role of renewable energy in climate stabilization: results from the EMF27 scenarios

Abstract: This paper uses the EMF27 scenarios to explore the role of renewable energy (RE) in climate change mitigation. Currently RE supplies almost 20 % of global electricity demand. Almost all EMF27 mitigation scenarios show a strong increase in renewable power production, with a substantial ramp-up of wind and solar power deployment. In many scenarios, renewables are the most important long-term mitigation option for power supply. Wind energy is competitive even without climate policy, whereas the prospects of solar photovoltaics (PV) are highly contingent on the ambitiousness of climate policy. Bioenergy is an important and versatile energy carrier; however—with the exception of low temperature heat—there is less scope for renewables other than biomass for non-electric energy supply. Despite the important role of wind and solar power in climate change mitigation scenarios with full technology availability, limiting their deployment has a relatively small effect on mitigation costs, if nuclear and carbon capture and storage (CCS)—which can serve as substitutes in low-carbon power supply—are available. Limited bioenergy availability in combination with limited wind and solar power by contrast, results in a more substantial increase in mitigation costs. While a number of robust insights emerge, the results on renewable energy deployment levels vary considerably across the models. An in-depth analysis of a subset of EMF27 reveals substantial differences in modeling approaches and parameter assumptions. To a certain degree, differences in model results can be attributed to different assumptions about technology costs, resource potentials and systems integration.

A Review on the Effect of Large-scale PV Generation on Power Systems

Abstract: Because of human concern for energy security and environmental deterioration, making full use of renewable energy has been a global consensus Power generation with large-scale renewable energy such as solar and wind energy has become the development trend of new power systems, resulting in increasingly prominent impact on power systems Therefore, great concerns are given from academic and engineering areas of all countries The purpose of this paper is to review the globe status of large-scale photovoltaic(PV) power generation, explore the factors affecting the interaction between solar power generation and power system, refine academic and engineering problems, and propose ideas for future research and development From the perspective of power system planning, simulation, dispatching and control, this paper discusses the modeling and simulation of large-scale photovoltaic power generation, impacts of large scale PV integration on dynamic and static characteristics of power system, and key technologies about large scale PV power generation delivery and consumption Meanwhile, suggestions for further research are proposed from the authors' point of view, offering reference for readers

Modeling of solar PV module and maximum power point tracking using ANFIS

Abstract: Solar energy, at the present time is considered as an important source in electricity generation. Electricity from the solar energy can be generated using solar photovoltaic (PV) modules. The maximization of solar power extracted from a PV module is of special concern as its efficiency is very low. The output power of a PV module is highly dependent on the geographical location and weather conditions such as solar irradiation, shading and temperature. To obtain maximum power from PV module, photovoltaic power system usually requires maximum power point tracking (MPPT) controller. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) based maximum power point tracker for PV module has been presented. To extract maximum power, a DC–DC boost converter is connected between the PV module and the load. The duty cycle of DC–DC boost converter is modified with the help of the ANFIS reference model, so that maximum power is transferred to load. Due to the complexity of the tracker mechanism and non-linear nature of photovoltaic system, the artificial intelligence based technique, especially the ANFIS method, is used in this paper. In order to observe the maximum available power of PV module, the ANFIS reference model directly takes in operating temperature and irradiance level as input. The response of proposed ANFIS based control system shows accuracy and fast response. The simulation result reveals that the maximum power point is tracked satisfactorily for varying irradiance and temperature of PV module. Simulation results are provided to validate the concept.

Direct Band Gap Silicon Allotropes

Abstract: Elemental silicon has a large impact on the economy of the modern world and is of fundamental importance in the technological field, particularly in solar cell industry. The great demand of society for new clean energy and the shortcomings of the current silicon solar cells are calling for new materials that can make full use of the solar power. In this paper, six metastable allotropes of silicon with direct or quasidirect band gaps of 0.39–1.25 eV are predicted by ab initio calculations at ambient pressure. Five of them possess band gaps within the optimal range for high converting efficiency from solar energy to electric power and also have better optical properties than the Si-I phase. These Si structures with different band gaps could be applied to multiple p–n junction photovoltaic modules.

Macro-site selection of wind/solar hybrid power station based on ELECTRE-II

Abstract: Currently, many defects have appeared in wind and solar power generation systems. Utilizing the complementary of wind and solar power generation will break the bottleneck of new energy development. How to select the site of wind/solar hybrid power station scientifically is a primary problem. First, the framework of the indicator system is obtained from the literature review and refined according to the resources evaluation standards and different perspectives of the various scholars. Then this paper selects seven wind/solar hybrid power stations which have been put into operation as the case study, weights the indicators through the method of order relations, and evaluates these seven regions via ELECTRE-II. The conclusions are consistent with the related research findings and have better correctness, proving the feasibility and effectiveness of the method. It may provide some theoretical basis for the macro-site selection of wind/solar hybrid power station.

Modeling Solar Radiation at the Earth's Surface: Recent Advances

Abstract: Solar radiation data is important for a wide range of applications, e.g. in engineering, agriculture, health sector, and in many fields of the natural sciences. A few examples showing the diversity of applications may include: architecture and building design, e.g. air conditioning and cooling systems; solar heating system design and use; solar power generation; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control; skin cancer research.

Identifying PV Module Mismatch Faults by a Thermography-Based Temperature Distribution Analysis

Abstract: Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.

A review of integrated solar combined cycle system (ISCCS) with a parabolic trough technology

Abstract: The huge amount of solar energy available on Earth׳s surface has heightened awareness in Concentrating Solar Power, and more particularly in hybrid concepts. The integrated solar combined cycle system (ISCCS) is one of the more promising hybrid configurations for converting solar energy into electricity and it might become the technology of choice in the near future. This article reviews the R&D activities and published studies since the introduction of such a concept in the 1990s. The review includes the current status and describes different hybridizations of solar energy with natural gas, coal and other renewable energy sources. Furthermore, it provides in-depth analysis of real and expected R&D finding.